Network analytics tools deepen with machine learning and AI

David Morton, director of networks and telecommunications for the University of Washington, manages a wireless network for three college campuses, three hospital sites and 30 additional clinics; several research locations; and up to 85,000 users connecting up to 200,000 devices. If anyone asked, he could pinpoint a single device and single user and know whether that person was standing inside a building or was walking outside on the way to class. What provides Morton such deep visibility are network analytics tools driven by machine learning and artificial intelligence principles. Users of the university's network expect it to always work, no matter how much usage grows, Morton said. Applying new analytics tools provides a much better look into network performance and helps the university keep up with demands.